COVID-19 antibody responses in individuals with natural immunity and with vaccination-induced immunity: a systematic review and meta-analysis

Background The COVID-19 pandemic has caused a large mortality and morbidity burden globally. For individuals, a strong immune response is the most effective means to block SARS-CoV-2 infection. To inform clinical case management of COVID-19, development of improved vaccines, and public health policy, a better understanding of antibody response dynamics and duration following SARS-CoV-2 infection and after vaccination is imperatively needed. Methods We systematically analyzed antibody response rates in naturally infected COVID-19 patients and vaccinated individuals. Specifically, we searched all published and pre-published literature between 1 December 2019 and 31 July 2023 using MeSH terms and “all field” terms comprising “COVID-19” or “SARS-CoV-2,” and “antibody response” or “immunity response” or “humoral immune.” We included experimental and observational studies that provided antibody positivity rates following natural COVID-19 infection or vaccination. A total of 44 studies reporting antibody positivity rate changes over time were included. Results The meta-analysis showed that within the first week after COVID-19 symptom onset/diagnosis or vaccination, antibody response rates in vaccinated individuals were lower than those in infected patients (p < 0.01), but no significant difference was observed from the second week to the sixth month. IgG, IgA, and IgM positivity rates increased during the first 3 weeks; thereafter, IgG positivity rates were maintained at a relatively high level, while the IgM seroconversion rate dropped. Conclusions Antibody production following vaccination might not occur as quickly or strongly as after natural infection, and the IgM antibody response was less persistent than the IgG response. Supplementary Information The online version contains supplementary material available at 10.1186/s13643-024-02597-y.

Table S2.MINORS quality assessment of the non-randomized studies.
Table S3.Cochrane quality assessment of the randomized studies.
Table S4.PRISMA checklist.Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread globally and caused a huge loss.By now, vaccination is the most effective public health method against this infectious disease.However, as some recent studies show, vaccine effectiveness declines so rapidly that the average protection effectiveness drops for 87.9% to 48.1% in a period of 8 months (1).
Differences of antibody responses to diverse types of vaccines has been reported (2,3), but few studies compare the vaccine-caused antibody responses with the virus-caused antibody responses.Here we want to research the differences between natural immunity response (includes responses in both symptomatic and asymptomatic patients) and artificial immunity response.We hope that this study will provide some inspire for vaccine development as well as policy strategies.

Objectives:
Our study aims to achieve the following objectives.To: 1. Compare the seropositivity levels of antibodies against SARS-CoV-2 in nature and artificial immunity responses.
2. Compare the overtime changes of antibody positive rates between the nature and artificial immunity responses.

Methods:
We want to review systematically using the key words 'COVID-19' or 'SARS-Cov-2' and 'antibody response' or 'immunity response' or 'humoral responses' to identify all the published and pre-publication studies.Then meta-analyses will be conducted in order to evaluate the association between antibody levels and immunity responses types (patients or vaccinee).

Expected Outcomes:
Main expected outcomes of our meta-analysis will include antibody seropositivity levels of different immunity types.According to a former study (4), the antibody outcomes will include seropositivity levels of pan-immunoglobulins, IgM, IgA, and IgG antibodies against SARS-CoV-2 nucleocapsid(N), and neutralising antibodies.[3] Yuan, Ping et al., Safety, tolerability, and immunogenicity of COVID-19 vaccines: a systematic review and meta-analysis, medRxiv (2020).
[4] He, Ren et al., Seroprevalence and humoral immune durability of anti-SARS-CoV-2 antibodies in Wuhan, China: a longitudinal, population-level, cross-sectional study, the Lancet (2021).Selection process 8 Specify the methods used to decide whether a study met the inclusion criteria of the review, including how many reviewers screened each record and each report retrieved, whether they worked independently, and if applicable, details of automation tools used in the process.

File S3. Data Extraction Form
Methods, 'search strategy'

Data collection process
9 Specify the methods used to collect data from reports, including how many reviewers collected data from each report, whether they worked independently, any processes for obtaining or confirming data from study investigators, and if applicable, details of automation tools used in the process.

Methods, 'Data extraction and outcomes'
Data items 10a List and define all outcomes for which data were sought.Specify whether all results that were compatible with each outcome domain in each study were sought (e.g. for all measures, time points, analyses), and if not, the methods used to decide which results to collect.

Methods, 'Data extraction and outcomes'
10b List and define all other variables for which data were sought (e.g.participant and intervention characteristics, funding sources).Describe any assumptions made about any missing or unclear information.

Methods, 'Data extraction and outcomes'
Study risk of bias assessment 11 Specify the methods used to assess risk of bias in the included studies, including details of the tool(s) used, how many reviewers assessed each study and whether they worked independently, and if applicable, details of automation tools used in the process.
Methods, 'Quality Assessment and Data analysis', paragraph 1-2 Effect measures 12 Specify for each outcome the effect measure(s) (e.g.risk ratio, mean difference) used in the synthesis or presentation of results.Methods, 'Quality Assessment and Data analysis', paragraph 3 Synthesis methods 13a Describe the processes used to decide which studies were eligible for each synthesis (e.g.tabulating the study intervention characteristics and comparing against the planned groups for each synthesis (item #5)).

N/A
13b Describe any methods required to prepare the data for presentation or synthesis, such as handling of missing summary statistics, or data conversions.Appendix Table S1 Risk of bias in studies 18 Present assessments of risk of bias for each included study.Table 1 Appendix Table S2 Results of individual studies

Methods
19 For all outcomes, present, for each study: (a) summary statistics for each group (where appropriate) and (b) an effect estimate and its precision (e.g.confidence/credible interval), ideally using structured tables or plots.Events: number of participants with detectable IgG antibody levels.Events: number of participants with detectable IgG antibody levels.Events: number of participants with detectable IgG antibody levels.Events: number of participants with detectable IgG antibody levels.Events: number of participants with detectable IgG antibody levels.Events: number of participants with detectable antibody levels.Events: number of participants with detectable antibody levels.Events: number of participants with detectable antibody levels.Events: number of participants with detectable antibody levels.Events: number of participants with detectable antibody levels.Events: number of participants with detectable antibody levels.Events: number of participants with detectable antibody levels.

Figure S1 .
Figure S1.(related to Figure 3) Forest plot of pooled IgG response rates at 8-14 days across

Figure S2 .
Figure S2.(related to Figure 3) Forest plot of pooled IgG response rates at 15-21 days across

Figure S3 .
Figure S3.(related to Figure 3) Forest plot of pooled IgG response rates at 22 days -1 month

Figure S4 .
Figure S4.(related to Figure 3) Forest plot of pooled IgG response rates at 1-2 months across

Figure S5 .
Figure S5.(related to Figure 3) Forest plot of pooled IgG response rates at 2-3 months across

Figure S6 .
Figure S6.(related to Figure 3) Forest plot of pooled IgG response rates at 3-6 months across

Figure S7 .
Figure S7.(related to Figure 3) Forest plot of pooled IgG response rates after 6 months

Figure S8 .
Figure S8.(related to Figure 5) Forest plot of pooled antibody response rates at 8-14 days

Figure S9 .
Figure S9.(related to Figure 5) Forest plot of pooled antibody response rates at 15-21 days

Figure S10 .
Figure S10.(related to Figure 5) Forest plot of pooled antibody response rates at 22 days -1

Figure S11 .
Figure S11.(related to Figure 5) Forest plot of pooled antibody response rates at 1-2 months

Figure S12 .
Figure S12.(related to Figure 5) Forest plot of pooled antibody response rates at 2-3 months

Figure S13 .
Figure S13.(related to Figure 5) Forest plot of pooled antibody response rates at 3-6 months

Figure S14 .
Figure S14.(related to Figure 5) Forest plot of pooled antibody response rates after 6 months

Figure S15 .
Figure S15.(related to Figure 2) Sensitivity analysis: excluding each study one at a time.

Figure S16 .
Figure S16.(related to Figure 4) Sensitivity analysis: excluding each study one at a time.

Figure S17 .
Figure S17.Funnel plots of publication bias and results of Egger's test.

Figure S1 .
Figure S1.(related to Figure 3) Forest plot of pooled IgG response rates at 8-14 days across

Figure S2 .
Figure S2.(related to Figure 3) Forest plot of pooled IgG response rates at 9-21 days across

Figure S3 .
Figure S3.(related to Figure 3) Forest plot of pooled IgG response rates at 22 days -1

Figure S4 .
Figure S4.(related to Figure 3) Forest plot of pooled IgG response rates at 1-2 months

Figure S5 .
Figure S5.(related to Figure 3) Forest plot of pooled IgG response rates at 2-3 months

Figure S6 .
Figure S6.(related to Figure 3) Forest plot of pooled IgG response rates at 3-6 months

Figure S7 .
Figure S7.(related to Figure 3) Forest plot of pooled IgG response rates after 6 months

Figure S8 .
Figure S8.(related to Figure 5) Forest plot of pooled antibody response rates at 8-14 days

Figure S9 .
Figure S9.(related to Figure 5) Forest plot of pooled antibody response rates at 15-21 days

Figure S10 .
Figure S10.(related to Figure 5) Forest plot of pooled antibody response rates at 22 days -1

Figure S11 .
Figure S11.(related to Figure 5) Forest plot of pooled antibody response rates at 1-2 months

Figure S12 .
Figure S12.(related to Figure 5) Forest plot of pooled antibody response rates at 2-3

Figure S13 .
Figure S13.(related to Figure 5) Forest plot of pooled antibody response rates at 3-6

Figure S14 .
Figure S14.(related to Figure 5) Forest plot of pooled antibody response rates after 6

Figure S15 .
Figure S15.(related to Figure 2) Sensitivity analysis: excluding each study one at a time.

Figure S16 .
Figure S16.(related to Figure 4) Sensitivity analysis: excluding each study one at a time.

Figure S17 .
Figure S17.Funnel plots of publication bias and results of Egger's test.

Risk of bias assessment: for non-randomized study only
* Additional Criteria for comparative study Notes: The items are scored 0 (not reported), 1 (reported but inadequate) or 2 (reported and adequate).

Table S1 .
Demographic characteristics of the Included Studies.

Table S2 .
MINORS Quality Assessment of the non-randomized Studies[24].For comparative studies, a score of <= 16 would be considered poor quality, 17-22 as moderate quality, and 23-24 as good quality.
Notes: The items are scored 0 (not reported), 1 (reported but inadequate) or 2 (reported and adequate).For non-comparative studies, a score of <= 10 would be considered poor quality, 11-14 as moderate quality, and 15-16 as good quality.

Table S3 .
Cochrane Quality Assessment of the randomized Studies [78].

Table 1
Describe any methods used to synthesize results and provide a rationale for the choice(s).If meta-analysis was performed, describe the model(s), method(s) to identify the presence and extent of statistical heterogeneity, and software package(s) used.Describe the results of the search and selection process, from the number of records identified in the search to the number of studies included in the review, ideally using a flow diagram.
Present results of all statistical syntheses conducted.If meta-analysis was done, present for each the summary estimate and its precision (e.g.confidence/credible interval) and measures of statistical heterogeneity.If comparing groups, describe the direction of the effect.Support25 Describe sources of financial or non-financial support for the review, and the role of the funders or sponsors in the review.Report which of the following are publicly available and where they can be found: template data collection forms; data extracted from included studies; data used for all analyses; analytic code; any other materials used in the review.